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80 lines
2.2 KiB
80 lines
2.2 KiB
#include "perf_precomp.hpp" |
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namespace cvtest |
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{ |
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using std::tr1::tuple; |
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using std::tr1::get; |
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using std::tr1::make_tuple; |
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using std::make_pair; |
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using namespace perf; |
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using namespace testing; |
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using namespace cv; |
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using namespace cv::dnn; |
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enum {STRIDE_OFF = 1, STRIDE_ON = 2}; |
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CV_ENUM(StrideSize, STRIDE_OFF, STRIDE_ON); |
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enum {GROUP_OFF = 1, GROUP_2 = 2}; |
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CV_ENUM(GroupSize, GROUP_OFF, GROUP_2); |
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//Squared Size |
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#define SSZ(n) cv::Size(n, n) |
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typedef std::pair<BlobShape, int> InpShapeNumOut; |
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typedef tuple<Size, InpShapeNumOut, GroupSize, StrideSize> ConvParam; //kernel_size, inp shape, groups, stride |
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typedef TestBaseWithParam<ConvParam> ConvolutionPerfTest; |
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PERF_TEST_P( ConvolutionPerfTest, perf, Combine( |
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Values(Size(1, 1), Size(3, 3), Size(5, 5), Size(11, 11)), |
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Values(make_pair(BlobShape(1, 4, 224, 224), 64), |
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make_pair(BlobShape(1, 64, 112, 122), 128), |
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make_pair(BlobShape(1, 256, 28, 28), 512)), |
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GroupSize::all(), |
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StrideSize::all()) |
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) |
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{ |
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RNG rng(0); |
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ConvParam params = GetParam(); |
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int ksz = get<0>(params).width; |
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BlobShape inpShape = get<1>(params).first; |
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int outCn = get<1>(params).second; |
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int groups = get<2>(params); |
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int stride = (ksz >= 11) ? 4 : get<3>(params); |
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int inpCn = inpShape[1]; |
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Blob wgtBlob(BlobShape(outCn, inpCn/groups, ksz, ksz)), biasBlob(BlobShape(outCn, 1, 1, 1)); |
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Blob inpBlob(inpShape); |
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rng.fill(biasBlob.matRef(), RNG::UNIFORM, -1, +1); |
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rng.fill(wgtBlob.matRef(), RNG::UNIFORM, -1, +1); |
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rng.fill(inpBlob.matRef(), RNG::UNIFORM, -1, +1); |
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LayerParams lp; |
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lp.set("num_output", outCn); |
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lp.set("group", groups); |
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lp.set("stride", stride); |
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lp.set("kernel_size", ksz); |
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lp.blobs.reserve(2); |
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lp.blobs.push_back(wgtBlob); |
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lp.blobs.push_back(biasBlob); |
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std::vector<Blob*> inpBlobs(1, &inpBlob); |
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std::vector<Blob> outBlobs; |
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cv::setNumThreads(cv::getNumberOfCPUs()); |
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Ptr<Layer> layer = cv::dnn::LayerFactory::createLayerInstance("Convolution", lp); |
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layer->allocate(inpBlobs, outBlobs); |
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declare.in(inpBlob.matRef(), wgtBlob.matRef(), WARMUP_RNG).out(outBlobs[0].matRef()).tbb_threads(cv::getNumThreads()); |
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TEST_CYCLE_N(10) |
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{ |
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layer->forward(inpBlobs, outBlobs); |
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} |
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SANITY_CHECK_NOTHING(); |
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} |
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} |